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Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter

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Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter

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dc.contributor.author Trull, Óscar es_ES
dc.contributor.author García-Díaz, J. Carlos es_ES
dc.contributor.author Troncoso, Alicia es_ES
dc.date.accessioned 2020-12-01T04:32:33Z
dc.date.available 2020-12-01T04:32:33Z
dc.date.issued 2019-03-02 es_ES
dc.identifier.uri http://hdl.handle.net/10251/156110
dc.description.abstract [EN] Forecasting electricity demand through time series is a tool used by transmission system operators to establish future operating conditions. The accuracy of these forecasts is essential for the precise development of activity. However, the accuracy of the forecasts is enormously subject to the calendar effect. The multiple seasonal Holt-Winters models are widely used due to the great precision and simplicity that they offer. Usually, these models relate this calendar effect to external variables that contribute to modification of their forecasts a posteriori. In this work, a new point of view is presented, where the calendar effect constitutes a built-in part of the Holt-Winters model. In particular, the proposed model incorporates discrete-interval moving seasonalities. Moreover, a clear example of the application of this methodology to situations that are difficult to treat, such as the days of Easter, is presented. The results show that the proposed model performs well, outperforming the regular Holt-Winters model and other methods such as artificial neural networks and Exponential Smoothing State Space Model with Box-Cox Transformation, ARMA Errors, Trend and Seasonal Components (TBATS) methods. es_ES
dc.description.sponsorship The authors would like to thank the Spanish Ministry of Economy and Competitiveness for the support under project TIN2017-8888209C2-1-R. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Energies es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Time series es_ES
dc.subject Forecasting es_ES
dc.subject Exponential smoothing es_ES
dc.subject Electricity demand es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/en12061083 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-88209-C2-1-R/ES/BIG DATA STREAMING: ANALISIS DE DATOS MASIVOS CONTINUOS. MODELOS PREDICTIVOS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Trull, Ó.; García-Díaz, JC.; Troncoso, A. (2019). Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter. Energies. 12(6):1-16. https://doi.org/10.3390/en12061083 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/en12061083 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 16 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 6 es_ES
dc.identifier.eissn 1996-1073 es_ES
dc.relation.pasarela S\386252 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
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